np.linspace allows you to define how many values you get including the specified min and max value. It infers the stepsize:
>>> np.linspace(0,1,11)
array([0. , 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1. ])
np.arange allows you to define the stepsize and infers the number of steps(the number of values you get).
>>> np.arange(0,1,.1)
array([0. , 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9])
contributions from user2357112:
np.arange excludes the maximum value unless rounding error makes it do otherwise.
For example, the following results occur due to rounding error:
>>> numpy.arange(1, 1.3, 0.1)
array([1. , 1.1, 1.2, 1.3])
You can exclude the stop value (in our case 1.3) using endpoint=False:
>>> numpy.linspace(1, 1.3, 3, endpoint=False)
array([1. , 1.1, 1.2])
np.linspace allows you to define how many values you get including the specified min and max value. It infers the stepsize:
>>> np.linspace(0,1,11)
array([0. , 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1. ])
np.arange allows you to define the stepsize and infers the number of steps(the number of values you get).
>>> np.arange(0,1,.1)
array([0. , 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9])
contributions from user2357112:
np.arange excludes the maximum value unless rounding error makes it do otherwise.
For example, the following results occur due to rounding error:
>>> numpy.arange(1, 1.3, 0.1)
array([1. , 1.1, 1.2, 1.3])
You can exclude the stop value (in our case 1.3) using endpoint=False:
>>> numpy.linspace(1, 1.3, 3, endpoint=False)
array([1. , 1.1, 1.2])
np.arange(start, stop, step)
np.linspace(start,stop,number)
Example:
np.arange(0,10,2) o/p --> array([0,2,4,6,8])
np.linspace(0,10,2) o/p --> array([0., 10.])
linear algebra - How to express the Pythons' NumPy linspace or arange arrays mathematically? - Mathematics Stack Exchange
Numpy.arange() decimal precision
How to make a list or array of numbers covering a wide range [1e-6,1e-5...1e6]?
Difference between range and arange?
numpy.arange
numpy.arange([start, ]stop, [step, ]dtype=None)Return evenly spaced values within a given interval.
Values are generated within the half-open interval [start, stop) (in other words, the interval including start but excluding stop). For integer arguments the function is equivalent to the Python built-in range function, but returns an ndarray rather than a list.
(Source)
So they are the same when using integers (except for the return type), but numpy's version can use other variable types.
If you're using Python 3, though, note that range has changed and now returns an iterator instead of a list. (Explained here.)
Videos
(I will ignore the difference between reals and floats here - not that it is unimportant), where 
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, or (not quite fully formally):
Hello, I am fairly new to python and have been using it for homework and school projects as of late. However, I have been noticing a trend when I am attempting to use numpy's arrange feature for creating lists. I can create the list and print it to the command window in spyder and everything seems fine, but when I go to use the elements of the list, extra decimals seemed to be added to the end of some of the elements.
This is what I expect to happen in Spyder
import numpy as np X=np.arange(0,1.1,0.1) print(X) >>[0. 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1. ]
But when I use this list for naming (File names, plot titles, and legends) I get extra decimals such as 0.30000000000000004
Which is really confusing me. I figured out that I can use the round function in python and just round the numbers off to rid of the extra decimals, but this is becoming very tedious and isn't what I would expect.
Is there something I am doing wrong or is this just an innate feature of numpy.arange()? Any comments or tips are appreciated!